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View synthesis methods using implicit continuous shape representations learned from a set of images, such as the Neural Radiance Field (NeRF) method, have gained increasing attention due to their high quality imagery and scalability to high resolution. However, the heavy computation required by its volumetric approach prevents NeRF from being useful in practice; minutes are taken to render a single image of a few megapixels. Now, an image of a scene can be rendered in a level-of-detail manner, so we posit that a complicated region of the scene should be represented by a large neural network while a small neural network is capable of encoding a simple region, enabling a balance between efficiency and quality. Recursive-NeRF is our embodiment of this idea, providing an efficient and adaptive rendering and training approach for NeRF. The core of Recursive-NeRF learns uncertainties for query coordinates, representing the quality of the predicted color and volumetric intensity at each level. Only query coordinates with high uncertainties are forwarded to the next level to a bigger neural network with a more powerful representational capability. The final rendered image is a composition of results from neural networks of all levels. Our evaluation on public datasets and a large-scale scene dataset we collected shows that Recursive-NeRF is more efficient than NeRF while providing state-of-the-art quality. The code will be available at https://github.com/Gword/Recursive-NeRF.

Hypergraphs are useful mathematical models for describing complex relationships among members of a structured graph, while hyperdigraphs serve as a generalization that can encode asymmetric relationships in the data. However, obtaining topological information directly from hyperdigraphs remains a challenge. To address this issue, we introduce hyperdigraph homology in this work. We also propose topological hyperdigraph Laplacians, which can extract both harmonic spectra and non-harmonic spectra from directed and internally organized data. Moreover, we introduce persistent hyperdigraph homology and persistent hyperdigraph Laplacians through filtration, enabling the capture of topological persistence and homotopic shape evolution of directed and structured data across multiple scales. The proposed methods offer new multiscale algebraic topology tools for topological data analysis.

Background: Cardioprotection is valued in radiotherapy for patients with left-sided breast cancer. Deep inspiration breath-hold (DIBH) technique can achieve cardioprotection well. However, during DIBH, the extent to which the heart enters the radiation field is affected by the movement of the thorax and diaphragm. The aim of this study was to analyze the correlation between the maximum distance of the heart entering the field (maximum heart distance, MHD) and thoracic diameter changes and diaphragmatic descent in left-sided breast cancer patients during DIBH., Patients and Methods: Ninety-eight patients with left-sided breast cancer were included in this retrospective study. They performed simulation in Sentinel-guided DIBH, and two sets of CT images were collected under both free breathing (FB) and DIBH, and diaphragm positions, anteroposterior thoracic diameter (ATD), transverse thoracic diameter (TTD), gating window level (GWL), and MHD were measured, and the change (Δ) of each parameter in DIBH relative to that in FB were calculated. Pearson or Spearman test were used to analyze the correlation between ΔMHD and the changes in other parameters., Results: For all patients with DIBH, the average of ΔMHD was -8.3 mm, and the average of ΔATD and ΔTTD were 11.0 and 8.6 mm, and the median of both left diaphragmatic descent (LDD) and right diaphragmatic descent (RDD) were 35.0 mm, and the median of GWL was 11.1 mm. The correlation coefficients between MHD decrease (ΔMHD) and LDD, RDD, and ΔTTD were -0.430 (p = 0.000), -0.592 (p = 0.000) and 0.208 (p = 0.040), respectively, but not significantly correlated with ΔATD or GWL., Conclusions: The MHD decrease showed a moderate correlation with diaphragmatic descent In Sentinel-guided DIBH for patients with left-sided breast cancer, while there was a weak or no correlation with thoracic diameter changes or GWL. Abdominal breathing can lower diaphragm more and may be more beneficial to the heart stay away from tangential field., (© 2023 He-Gou Wu et al., published by Sciendo.)

The birth of ChatGPT, a cutting-edge language model-based chatbot developed by OpenAI, ushered in a new era in AI. However, due to potential pitfalls, its role in rigorous scientific research is not clear yet. This paper vividly showcases its innovative application within the field of drug discovery. Focused specifically on developing anticocaine addiction drugs, the study employs GPT-4 as a virtual guide, offering strategic and methodological insights to researchers working on generative models for drug candidates. The primary objective is to generate optimal drug-like molecules with desired properties. By leveraging the capabilities of ChatGPT, the study introduces a novel approach to the drug discovery process. This symbiotic partnership between AI and researchers transforms how drug development is approached. Chatbots become facilitators, steering researchers toward innovative methodologies and productive paths for creating effective drug candidates. This research sheds light on the collaborative synergy between human expertise and AI assistance, wherein ChatGPT's cognitive abilities enhance the design and development of pharmaceutical solutions. This paper not only explores the integration of advanced AI in drug discovery but also reimagines the landscape by advocating for AI-powered chatbots as trailblazers in revolutionizing therapeutic innovation.

Background: Single-cell RNA sequencing, also known as scRNA-seq, is a method profiling cell populations on an individual cell basis. It is particularly useful for more deeply understanding cell behavior in a complicated tumor microenvironment. Although several previous studies have examined scRNA-seq for hepatocellular carcinoma (HCC) tissues, no one has tested and analyzed HCC with different stages., Methods: In this investigation, immune cells isolated from surrounding normal tissues and cancer tissues from 3 II-stage and 4 III-stage HCC cases were subjected to deep scRNA-seq. The analysis included 15 samples. We distinguished developmentally relevant trajectories, unique immune cell subtypes, and enriched pathways regarding differential genes. Western blot and co-immunoprecipitation were performed to demonstrate the interaction between fatty acid binding protein 1 (FABP1) and peroxisome proliferator-activated receptor gamma(PPARG). In vivo experiments were performed in a C57BL/6 mouse model of HCC established via subcutaneous injection., Results: FABP1 was discovered to be overexpressed in tumor-associated macrophages (TAMs) with III-stage HCC tissues compared with II-stage HCC tissues. This finding was fully supported by immunofluorescence detection in significant amounts of HCC human samples. FABP1 deficiency in TAMs inhibited HCC progression in vitro. Mechanistically, FABP1 interacted with PPARG/CD36 in TAMs to increase fatty acid oxidation in HCC. When compared with C57BL/6 mice of the wild type, tumors in FABP1-/- mice consistently showed attenuation. The FABP1-/- group's relative proportion of regulatory T cells and natural killer cells showed a downward trend, while dendritic cells, M1 macrophages, and B cells showed an upward trend, according to the results of mass cytometry. In further clinical translation, we found that orlistat significantly inhibited FABP1 activity, while the combination of anti-programmed cell death 1(PD-1) could synergistically treat HCC progression. Liposomes loaded with orlistat and connected with IR780 probe could further enhance the therapeutic effect of orlistat and visualize drug metabolism in vivo., Conclusions: ScRNA-seq atlas revealed an FABP1-dependent immunosuppressive environment in HCC. Orlistat significantly inhibited FABP1 activity, while the combination of anti-PD-1 could synergistically treat HCC progression. This study identified new treatment targets and strategies for HCC progression, contributing to patients with advanced HCC from new perspectives., Competing Interests: Competing interests: No, there are no competing interests., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Purpose: This study aimed to assess the prognostic and predictive value of a circulating hematological signature (CHS) and to develop a CHS-based nomogram for predicting prognosis and guiding individualized chemotherapy in non-metastatic nasopharyngeal carcinoma (NPC) patients., Patients and Methods: NPC patients were recruited between January 2014 and December 2017 at the Jiangxi Cancer Hospital. The CHS was constructed based on a series of hematological indicators. The nomogram was developed by CHS and clinical factors., Results: A total of 779 patients were included. Three biomarkers were selected by least absolute shrinkage and selection operator regression, including prognostic nutritional index, albumin-to-fibrinogen ratio, and prealbumin-to-fibrinogen ratio, were used to construct the CHS. The patients in the low-CHS group had better 5-year DMFS and OS than those in the high-CHS group in the training (DMFS: 85.0% vs 56.6%, p <0.001; OS: 90.3% vs 65.4%, p <0.001) and validation cohorts (DMFS: 92.3% vs 43.6%, p <0.001; OS: 92.1% vs 65.5%, p <0.001). The nomogram&#95;CHS showed better performance than clinical stage in predicting distant metastasis (concordance index: 0.728 vs 0.646). In the low-TRS (total risk scores) group, the patients received RT alone, CCRT and IC plus CCRT had similar 5-year DMFS and OS ( p >0.05). In the middle-TRS group, the patients received RT alone had worse 5-year DMFS (58.7% vs 80.8% vs 90.8%, p =0.002) and OS (75.0% vs 94.1% vs 95.0%, p =0.001) than those received CCRT or IC plus CCRT. In the high-TRS group, the patients received RT alone and CCRT had worse 5-year DMFS (18.6% vs 31.3% vs 81.5%, p <0.001) and OS (26.9% vs 53.2% vs 88.8%, p <0.001) than those received IC plus CCRT., Conclusion: The developed nomogram&#95;CHS had satisfactory prognostic accuracy in NPC patients and may individualize risk estimation to facilitate the identification of suitable IC candidates., Competing Interests: The authors report no conflicts of interest in this work., (© 2023 Chen et al.)

Introduction: To date, an increasing number of studies have revealed that GP73 may have prognostic value in liver cancer. However, most of the studies evaluated serum GP73, and the results regarding the prognostic value of tGP73 in liver cancer are still controversial. Therefore, in this meta-analysis, we aimed to determine whether tGP73 has any prognostic value in patients with HCC., Materials and Methods: Relevant publications were searched for in PubMed, EMBASE, OVID, the Cochrane Library, and the Web of Science databases up to March 2023. The hazard ratio (HR) or odds ratio (OR) with corresponding 95% confidence intervals (95% CIs) of eligible studies were assessed by fixed-effects or random-effects models. In addition, subgroup analyses were conducted to investigate the possible causes of heterogeneity, and publication bias analysis was also performed to assess the reliability of the meta-analysis results., Results: A total of 10 studies were included. These studies included 1569 HCC patients, and a meta-analysis was performed. The results of our meta-analysis showed that higher GP73 expression levels were significantly associated with poorer OS (HR = 1.87, 95% CI: 1.41-2.48, P < 0.0001, I 2  = 58%). However, there was no significant correlation between high GP73 expression and disease-free survival (DFS) (HR: 1.43, 95% CI: 0.93-2.33, P = 0.100). In addition, abnormal GP73 expression was also related to higher tumour tissue differentiation grade (OR = 3.03, 95% CI = 2.01-4.57, P < 0.0001, I 2  = 89%), later tumour stage (OR = 5.89, 95% CI = 2.31-14.99, P < 0.0001, I 2  = 0%), vascular invasion (OR = 1.72, 95% CI = 1.12-2.64, P = 0.010, I 2  = 0%), multiple tumours (OR = 2.44, 95% CI = 1.37-3.68, P = 0.001, I 2  = 44%) and early postoperative tumour recurrence (OR = 1.92, 95% CI = 1.10-3.28, P = 0.020, I 2  = 62%)., Conclusions: The meta-analysis showed that the overexpression of GP73 may be related to a poor prognosis of HCC, and it may also have a predictive effect on the invasion and metastasis of HCC., (© 2023. The Author(s).)

Background: A series of long non-coding RNAs (lncRNAs) have been reported to play a crucial role in cancer biology. Some previous studies report that lncRNA CDKN2B-AS1 is involved in some human malignancies. However, its role in hepatocellular carcinoma (HCC) has not been fully deciphered., Aim: To decipher the role of CDKN2B-AS1 in the progression of HCC., Methods: CDKN2B-AS1 expression in HCC was detected by quantitative real-time polymerase chain reaction. The malignant phenotypes of Li-7 and SNU-182 cells were detected by the CCK-8 method, EdU method, and flow cytometry, respectively. RNA immunoprecipitation was executed to confirm the interaction between CDKN2B-AS1 and E2F transcription factor 1 (E2F1). Luciferase reporter assay and chromatin immunoprecipitation were performed to verify the binding of E2F1 to the promoter of G protein subunit alpha Z (GNAZ). E2F1 and GNAZ were detected by western blot in HCC cells., Results: In HCC tissues, CDKN2B-AS1 was upregulated. Depletion of CDKN2B-AS1 inhibited the proliferation of HCC cells, and the depletion of CDKN2B-AS1 also induced cell cycle arrest and apoptosis. CDKN2B-AS1 could interact with E2F1. Depletion of CDKN2B-AS1 inhibited the binding of E2F1 to the GNAZ promoter region. Overexpression of E2F1 reversed the biological effects of depletion of CDKN2B-AS1 on the malignant behaviors of HCC cells., Conclusion: CDKN2B-AS1 recruits E2F1 to facilitate GNAZ transcription to promote HCC progression., Competing Interests: Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article., (©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.)

Patent ductus arteriosus (PDA) is a common congenital heart disease. CITED2 plays an important role in the development of the heart, and genetic variants in its coding region are significantly associated with cardiac malformations. However, the role of variants in the promoter region of CITED2 in the development of PDA remains unclear. We extracted the peripheral blood of 646 subjects (including 353 PDA patients and 293 unrelated healthy controls) for sequencing. We identified 13 promoter variants of the CITED2 gene (including 2 novel heterozygous variants). Of the 13 variants, 10 were found only in PDA patients. In mouse cardiomyocytes (HL-1) and rat cardiac myocytes (RCM), the transcriptional activity of the CITED2 gene promoter was significantly changed by the variants ( p < 0.05). The results of the experiments of electrophoretic mobility indicated that these variants may affect the transcription of the CITED2 gene by influencing the binding ability of transcription factors. These results, combined with the JASPAR database analysis, showed that the destruction/production of transcription factor binding sites due to the variants in the promoter region of the CITED2 gene may directly or indirectly affect the binding ability of transcription factors. Our results suggest for the first time that variants at the CITED2 promoter region may cause low expression of CITED2 protein related to the formation of PDA.

In the mammalian visual system, the ventral lateral geniculate nucleus (vLGN) of the thalamus receives salient visual input from the retina and sends prominent GABAergic axons to the superior colliculus (SC). However, whether and how vLGN contributes to fundamental visual information processing remains largely unclear. Here, we report in mice that vLGN facilitates visually-guided approaching behavior mediated by the lateral SC and enhances the sensitivity of visual object detection. This can be attributed to the extremely broad spatial integration of vLGN neurons, as reflected in their much lower preferred spatial frequencies and broader spatial receptive fields than SC neurons. Through GABAergic thalamocollicular projections, vLGN specifically exerts prominent surround suppression of visuospatial processing in SC, leading to a fine tuning of SC preferences to higher spatial frequencies and smaller objects in a context-dependent manner. Thus, as an essential component of the central visual processing pathway, vLGN serves to refine and contextually modulate visuospatial processing in SC-mediated visuomotor behaviors via visually-driven long-range feedforward inhibition., (© 2023. The Author(s).)

The incidence rate of colorectal cancer (CRC) has been increasing and poses severe threats to human health worldwide and developing effective treatment strategies remains an urgent task. In this study, Chaetoglobosin A (ChA), an endophytic fungal metabolite from the medicinal herb-derived fungus Chaetomium globosum Km1126, was identified as a potent and selective antitumor agent in human CRC. ChA induced growth inhibition of CRC cells in a concentration-dependent manner but did not impair the viability of normal colon cells. ChA triggered mitochondrial intrinsic and caspase-dependent apoptotic cell death. In addition, apoptosis antibody array analysis revealed that expression of Heme oxygenase-1 (HO-1) was significantly increased by ChA. Inhibition of HO-1 increased the sensitivity of CRC cells to ChA, suggesting HO-1 may play a protective role in ChA-mediated cell death. ChA induced cell apoptosis via the induction of reactive oxygen species (ROS) and ROS scavenger (NAC) prevented ChA-induced cell death, mitochondrial dysfunction, and HO-1 activation. ChA promoted the activation of c-Jun N-terminal kinase (JNK), and co-administration of JNK inhibitor or siRNA markedly reversed ChA-mediated apoptosis. ChA significantly decreased the tumor growth without eliciting any organ toxicity or affecting the body weight of the CRC xenograft mice. This is the first study to demonstrate that ChA exhibits promising anti-cancer properties against human CRC both in vitro and in vivo. ChA is a potential therapeutic agent worthy of further development in clinical trials for cancer treatment., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Objective: The aim of this study was to elucidate the mechanism of beraprost sodium (BPS) in the intervention of myocardial fibrosis after myocardial infarction (MI) through glycogen synthase kinase-3β (GSK-3β) and to provide new ideas for intervention in myocardial fibrosis., Materials and Methods: MI model rats given BPS and cardiac fibroblasts (CFs) treated with BPS and TGF-β. HE staining and Masson staining were used to detect the pathological changes of myocardial tissue. Fibrotic markers were detected by immunohistochemical staining. The expressions of GSK-3β, cAMP response element binding protein (CREB), and p-CREB were analyzed by qPCR and western blot analysis. EDU staining was used to detect the proliferation of CFs. The promoter activity of GSK-3β was detected by luciferase assay. Chromatin immunoprecipitation assay was used to detect the binding levels of GSK-3β promoter and Y-box binding protein 1 (YBX1). The levels of intracellular cyclic adenosine monophosphate (cAMP) were analyzed by enzyme-linked immunosorbent assay (ELISA)., Results: After operation, BPS improved myocardial fibrosis and upregulated GSK-3β protein expression in male SD rats. BPS can down-regulate α-smooth muscle actin (α-SMA) level and up-regulate GSK-3β protein expression in CFs after TGF-β stimulation. Furthermore, GSK-3β knockdown can reverse the effect of BPS on TGF-β-activated CFs, enhance α-SMA expression, and promote the proliferation of CFs. BPS could regulate GSK-3β expression by promoting the binding of GSK-3β promoter to YBX1. BPS induced upregulation of p-CREB and cAMP, resulting in reduced fibrosis, which was reversed by the knockdown of GSK-3β or prostaglandin receptor (IPR) antagonists., Conclusion: BPS treatment increased the binding of YBX1 to the GSK-3β promoter, and GSK-3β protein expression was upregulated, which further caused the upregulation of p-CREB and cAMP, and finally inhibited myocardial fibrosis., (© 2023 The Authors. Immunity, Inflammation and Disease published by John Wiley & Sons Ltd.)

Oral dysbiosis contributes to periodontitis and has implications for systemic diseases. Diabetes mellitus is a common metabolic disorder characterized by impaired glucose regulation. AMP-activated protein kinase (AMPK) plays a vital role in regulating glucose uptake and glycogenesis in the liver. This study aimed to investigate the association between periodontal bacteria and diabetes mellitus. A clinical trial was conducted to explore the association between oral bacteria and hyperglycemia. Additionally, we elucidated the molecular mechanisms by which periodontal bacteria cause insulin resistance. In the clinical trial, we discovered significant alterations in the expression levels of Fusobacterium nucleatum (Fn) and Tannerella forsythia (Tf) in patients with diabetes compared with healthy controls. Furthermore, Fn and Tf levels positively correlated with fasting blood glucose and glycated hemoglobin (HbA1C) levels. Moreover, we explored and elucidated the molecular mechanism by which Fusobacterium nucleatum culture filtrate (FNCF) induces cytokine release via the Toll-like receptor 2 (TLR2) signaling pathway in human gingival epithelial Smulow-Glickman (S-G) cells. This study investigated the effects of cytokines on insulin resistance pathways in liver cells. The use of an extracellular signal-regulated kinase (ERK) inhibitor (U0126) demonstrated that FNCF regulates the insulin receptor substrate 1 and protein kinase B (IRS1/AKT) signaling pathway, which affects key proteins involved in hepatic glycogen synthesis, including glycogen synthase kinase-3 beta (GSK3β) and glycogen synthase (GS), ultimately leading to insulin resistance. These findings suggest that ERK plays a crucial role in hepatocyte insulin resistance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.)

Purpose: Bulimia nervosa (BN) is characterized by recurrent binge-eating episodes and inappropriate compensatory behaviors. This study investigated alterations in resting-state surface-based neural activity in BN patients and explored correlations between brain activity and eating behavior., Methods: A total of 26 BN patients and 28 healthy controls were enrolled. Indirect measurement of cerebral cortical activity and functional connectivity (FC) analyses were performed in Surfstat. A principal component analysis (PCA) model was used to capture the commonalities within the behavioral questionnaires from the BN group., Results: Compared with the healthy control group, the BN group showed decreased surface-based two-dimensional regional homogeneity in the right superior parietal lobule (SPL). Additionally, the BN group showed decreased FC between the right SPL and the bilateral lingual gyrus and increased FC between the right SPL and the left caudate nucleus and right putamen. In the FC-behavior association analysis, the second principal component (PC2) was negatively correlated with FC between the right SPL and the left caudate nucleus. The third principal component (PC3) was negatively correlated with FC between the right SPL and the left lingual gyrus and positively correlated with FC between the right SPL and the right lingual gyrus., Conclusion: We revealed that the right SPL undergoes reorganization with respect to specific brain regions at the whole-brain level in BN. In addition, our results suggest a correlation between brain reorganization and maladaptive eating behavior. These findings may provide useful information to better understand the neural mechanisms of BN., Level of Evidence: V, descriptive study., (© 2023. The Author(s).)

The birth of ChatGPT, a cutting-edge language model-based chatbot developed by OpenAI, ushered in a new era in AI. However, due to potential pitfalls, its role in rigorous scientific research is not clear yet. This paper vividly showcases its innovative application within the field of drug discovery. Focused specifically on developing anti-cocaine addiction drugs, the study employs GPT-4 as a virtual guide, offering strategic and methodological insights to researchers working on generative models for drug candidates. The primary objective is to generate optimal drug-like molecules with desired properties. By leveraging the capabilities of ChatGPT, the study introduces a novel approach to the drug discovery process. This symbiotic partnership between AI and researchers transforms how drug development is approached. Chatbots become facilitators, steering researchers towards innovative methodologies and productive paths for creating effective drug candidates. This research sheds light on the collaborative synergy between human expertise and AI assistance, wherein ChatGPT's cognitive abilities enhance the design and development of potential pharmaceutical solutions. This paper not only explores the integration of advanced AI in drug discovery but also reimagines the landscape by advocating for AI-powered chatbots as trailblazers in revolutionizing therapeutic innovation., Competing Interests: Competing interests The authors declare no competing interests.

Live-cell transcriptomic recording can help reveal hidden cellular states that precede phenotypic transformation. Here we demonstrate the use of protein-based encapsulation for preserving samples of cytoplasmic RNAs inside living cells. These molecular time capsules (MTCs) can be induced to create time-stamped transcriptome snapshots, preserve RNAs after cellular transitions, and enable retrospective investigations of gene expression programs that drive distinct developmental trajectories. MTCs also open the possibility to uncover transcriptomes in difficult-to-reach conditions.

Objectives: This study aims to explore the pathogen-detected effect of mNGS technology and its clinical application in non-immunocompromised patients with severe pneumonia supported by vv-ECMO., Methods: A retrospective analysis was conducted on a cohort of 50 non-immunocompromised patients who received vv-ECMO support for severe pneumonia between January 2016 and December 2022. These patients were divided into two groups based on their discharge outcomes: the deterioration group (Group D), which included 31 cases, and the improvement group (Group I), consisting of 19 cases. Baseline characteristics and clinical data were collected and analyzed., Results: Among the 50 patients enrolled, Group D exhibited a higher prevalence of male patients (80.6% vs . 52.6%, p < 0.05), more smokers (54.8% vs . 21.1%, p < 0.05), and were older than those in Group I (55.16 ± 16.34 years vs . 42.32 ± 19.65 years, p < 0.05). Out of the 64 samples subjected to mNGS detection, 55 (85.9%) yielded positive results, with a positivity rate of 83.7% (36/43) in Group D and 90.5% (19/21) in Group I. By contrast, the positive rate through traditional culture stood at 64.9% (74/114). Among the 54 samples that underwent both culture and mNGS testing, 23 (42.6%) displayed consistent pathogen identification, 13 (24.1%) exhibited partial consistency, and 18 (33.3%) showed complete inconsistency. Among the last cases with complete inconsistency, 14 (77.8%) were culture-negative, while two (11.1%) were mNGS-negative, and the remaining two (11.1%) presented mismatches. Remarkably, mNGS surpassed traditional culture in pathogen identification (65 strains vs . 23 strains). Within these 65 strains, 56 were found in Group D, 26 in Group I, and 17 were overlapping strains. Interestingly, a diverse array of G+ bacteria, fungi, viruses, and special pathogens were exclusive to Group D. Furthermore, Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumoniae were more prevalent in Group D compared to Group I. Importantly, mNGS prompted antibiotic treatment adjustments in 26 patients (52.0%)., Conclusions: Compared with the conventional culture, mNGS demonstrated a higher positive rate, and emerges as a promising method for identifying mixed pathogens in non-immunodeficient patients with severe pneumonia supported by vv-ECMO. However, it is crucial to combine the interpretation of mNGS data with clinical information and traditional culture results for a comprehensive assessment., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Li, Niu, Zhao, Fu, Zhao, Huang and Li.)

Red tides occur every year in the Qinhuangdao sea area of China, including a variety of toxic algae and non-toxic algae. Toxic red tide algae have caused great damage to the marine aquaculture industry in China and seriously endangered human health, but most of non-toxic algae are important bait for marine plankton. Therefore, it is very important to identify the type of mixed red tide algae in Qinhuangdao sea area. In this paper, three-dimensional fluorescence spectroscopy and chemometrics were applied to the identification of typical toxic mixed red tide algae in Qinhuangdao. Firstly, the three-dimensional fluorescence spectrum data of typical mixed red tide algae in Qinhuangdao sea area were measured by f-7000 fluorescence spectrometer, and the contour map of algae samples was obtained. Secondly, the contour spectrum analysis is carried out to find the excitation wavelength of the peak position of the three-dimensional fluorescence spectrum and form the new three-dimensional fluorescence spectrum data selected by the feature interval. Then, the new three-dimensional fluorescence spectrum data are extracted by principal component analysis (PCA). Finally, the feature extraction data and the data without feature extraction are used as the input of the genetic optimization support vector machine (GA-SVM) and particle swarm optimization support vector machine (PSO-SVM) classification models, respectively, to obtain the classification model of mixed red tide algae, and the two feature extraction analysis methods and two classification algorithms are compared. The results show that the classification accuracy of the test set using the principal component feature extraction and GA-SVM classification method is 92.97 %, when the excitation wavelengths are 420 nm, 440 nm, 480 nm, 500 nm and 580 nm, and the emission wavelengths are 650-750 nm. Therefore, it is feasible and effective to apply the three-dimensional fluorescence spectrum characteristics and genetic optimization support vector machine classification method to the identification of toxic mixed red tide algae in Qinhuangdao sea area., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: Postoperative patients with Type A aortic dissection (TAAD) often experience severe inflammatory responses caused by multiple factors perioperatively. However, the effect of postoperative glucocorticoid (GC) use, which is a potent anti-inflammatory agent, on complications or all-cause mortality is unclear., Methods: Patients with TAAD who underwent surgical repair requiring deep hypothermic circulatory arrest between January 2020 and December 2021 were included in the study. Characteristics of patients treated with and without GCs were compared. The primary outcome was in-hospital mortality, and a composite secondary outcome was defined as in-hospital death or any major complications. Propensity score matching was used to balance baseline differences between groups. Kaplan-Meier curves were used to compare survival probability., Results: A total of 393 postoperative patients with TAAD were included in the study. Forty of them (10.2%) received GC treatment at a median daily methylprednisolone-equivalent dose of 0.6 mg/kg (0.4-0.7) for a median period of 2 (1-3) days. Patients on GCs had more intraoperative blood transfusions, higher postoperative APACHE II (12 vs 9, p = .004) and SOFA (9 vs 6, p < .001) scores, worse perioperative hepatic, renal and cardiac function. The in-hospital mortality in the matched cohort did not differ between groups [GC n = 11/40 (27.5%) versus Non-GC n = 19/80 (23.8%); p = .661]., Conclusions: The propensity to use GCs correlated with the critical status of the patient. However, low dose and short-term postoperative GC treatment did not reduce in-hospital mortality rates among patients with TAAD. A more appropriate regimen should be further investigated., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Objective: To discuss the hotspots and future trends of autophagy in traditional Chinese medicine (TCM) and provide a reference for researchers in this field., Method: Using visual analysis tools, metrological statistics and visual research on the pertinent literature in the area of autophagy use in TCM were undertaken in the core collection database of the Web of Science. By examining the authors, keywords, research circumstances, research hotspots, and trends of linked research, the use of autophagy in TCM was investigated., Results and Conclusions: A total of 916 studies were included, among which Beijing University Chinese Medicine was the largest number of advantageous research institutions, followed by Shanghai University Traditional Chinese Medicine and Guangzhou University Chinese Medicine.The keywords of literature research primarily comprise apoptosis, activation, inhibition, pathway, mechanism, oxidative stress, proliferation, NF-κB, cancer, mtor, etc. At present, the research on autophagy in the field of TCM is increasing on a year-to-year basis. The research has focused on the role played by TCM in malignant tumors, atherosclerosis, Alzheimer's disease through autophagy, and the regulation of autophagy signaling pathways (e.g., PI3K/AKT/mTOR signaling pathway, TLR4 signaling pathway,nrf2 signaling pathway and NF-κB signaling pathway). In the future, the therapeutic effect of TCM on chemotherapy-resistant tumor cells through autophagy pathway, the role of TCM mediating mitophagy and activating autophagy function, and the therapeutic effect of TCM components represented by luteolin on tumors, asthma, myocardial injury and other diseases through autophagy mechanism will be the research hotspots in the future., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors. Published by Elsevier Ltd.)

Protein engineering is an emerging field in biotechnology that has the potential to revolutionize various areas, such as antibody design, drug discovery, food security, ecology, and more. However, the mutational space involved is too vast to be handled through experimental means alone. Leveraging accumulative protein databases, machine learning (ML) models, particularly those based on natural language processing (NLP), have considerably expedited protein engineering. Moreover, advances in topological data analysis (TDA) and artificial intelligence-based protein structure prediction, such as AlphaFold2, have made more powerful structure-based ML-assisted protein engineering strategies possible. This review aims to offer a comprehensive, systematic, and indispensable set of methodological components, including TDA and NLP, for protein engineering and to facilitate their future development., (© The Author(s) 2023. Published by Oxford University Press.)

Opioid use disorder (OUD) has emerged as a significant global public health issue, necessitating the discovery of new medications. In this study, we propose a deep generative model that combines a stochastic differential equation (SDE)-based diffusion model with a pretrained autoencoder. The molecular generator enables efficient generation of molecules that target multiple opioid receptors, including mu, kappa, and delta. Additionally, we assess the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of the generated molecules to identify druglike compounds. We develop a molecular optimization approach to enhance the pharmacokinetic properties of some lead compounds. Advanced binding affinity predictors were built using molecular fingerprints, including autoencoder embeddings, transformer embeddings, and topological Laplacians. Our process yields druglike molecules that can be used in highly focused experimental studies to further evaluate their pharmacological effects. Our machine learning platform serves as a valuable tool for designing effective molecules to address OUD.

Hishimonus hamatus Kuoh is a leafhopper species native to China that feeds on Chinese jujube leaves. This leafhopper species has been verified to transmit jujube witches' broom (JWB) disease, caused by phytoplasma, a fatal plant pathogen, which belongs to the phytoplasma subgroup 16SrV-B. The transmission of JWB phytoplasma largely relies on the feeding behavior of piercing-sucking leafhoppers. However, the specific mechanisms behind how and why the infection of JWB influences the feeding behavior of these leafhoppers are not fully understood. To address this, a study was conducted to compare the feeding patterns of H. hamatus when feeding JWB-infested jujube leaves to healthy leaves using the electrical penetration graph (EPG) technique. Then, a widely targeted metabolome analysis was performed to identify differences in the metabolite composition of JWB-infected jujube leaves and that of healthy jujube leaves. The results of EPG analyses revealed that when feeding on JWB-infected jujube leaves, H. hamatus exhibited an increased frequency of phloem ingestion and spent longer in the phloem feeding phase compared to when feeding on healthy leaves. In addition, the results of metabolomic analyses showed that JWB-infected leaves accumulated higher levels of small-molecular carbohydrates, free amino acids, and free fatty acids, as well as lower levels of lignans, coumarins and triterpenoids compared to healthy leaves. The above results indicated that the H. hamatus preferentially fed on the phloem of infected leaves, which seems to be linked to the transmission of the JWB phytoplasma. The results of metabolomic analyses partially imply that the chemical compounds might play a role in making the infected leaves more attractive to H. hamatus for feeding., Competing Interests: The authors declare no conflicts of interest.

High-throughput deep mutational scanning (DMS) experiments have significantly impacted protein engineering, drug discovery, immunology, cancer biology, and evolutionary biology by enabling the systematic understanding of protein functions. However, the mutational space associated with proteins is astronomically large, making it overwhelming for current experimental capabilities. Therefore, alternative methods for DMS are imperative. We propose a topological deep learning (TDL) paradigm to facilitate in silico DMS. We utilize a new topological data analysis (TDA) technique based on the persistent spectral theory, also known as persistent Laplacian, to capture both topological invariants and the homotopic shape evolution of data. To validate our TDL-DMS model, we use SARS-CoV-2 datasets and show excellent accuracy and reliability for binding interface mutations. This finding is significant for SARS-CoV-2 variant forecasting and designing effective antibodies and vaccines. Our proposed model is expected to have a significant impact on drug discovery, vaccine design, precision medicine, and protein engineering., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Fluctuations in reproductive hormone levels are associated with mood disruptions in women, such as in postpartum and perimenopausal depression. However, the neural circuit mechanisms remain unclear. Here we report that medial preoptic area (MPOA) GABAergic neurons mediate multifaceted depressive-like behaviors in female mice after ovarian hormone withdrawal (HW), which can be attributed to downregulation of activity in Esr1 (estrogen receptor-1)-expressing GABAergic neurons. Enhancing activity of these neurons ameliorates depressive-like behaviors in HW-treated mice, whereas reducing their activity results in expression of these behaviors. Two separate subpopulations mediate different symptoms: a subpopulation projecting to the ventral tegmental area (VTA) mediates anhedonia and another projecting to the periaqueductal gray mediates immobility. These projections enhance activity of dopaminergic neurons in the VTA and serotonergic neurons in the dorsal raphe, respectively, with increased release of dopamine and serotonin, possibly through disinhibition mechanisms. Thus, the MPOA is a hub that mediates depressive-like behaviors resulting from transitions in reproductive hormone levels., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Optimizing catalysts for competitive photocatalytic reactions demand individually tailored band structure as well as intertwined interactions of light absorption, reaction activity, mass, and charge transport.  Here, a nanoparticulate host-guest structure is rationally designed that can exclusively fulfil and ideally control the aforestated uncompromising requisites for catalytic reactions. The all-inclusive model catalyst consists of porous Co 3 O 4 host and Zn x Cd 1- x S guest with controllable physicochemical properties enabled by self-assembled hybrid structure and continuously amenable band gap. The effective porous topology nanoassembly, both at the exterior and the interior pores of a porous metal-organic framework (MOF), maximizes spatially immobilized semiconductor nanoparticles toward high utilization of particulate heterojunctions for vital charge and reactant transfer. In conjunction, the zinc constituent band engineering is found to regulate the light/molecules absorption, band structure, and specific reaction intermediates energy to attain high photocatalytic CO 2 reduction selectivity. The optimal catalyst exhibits a H 2 -generation rate up to 6720 µmol g -1 h -1 and a CO production rate of 19.3 µmol g -1 h -1 . These findings provide insight into the design of discrete host-guest MOF-semiconductor hybrid system with readily modulated band structures and well-constructed heterojunctions for selective solar-to-chemical conversion., (© 2023 The Authors. Small published by Wiley-VCH GmbH.)

In this study, we examined the prognostic factors affecting outcomes following nerve grafting in high radial nerve injuries. Thirty-three patients with radial nerve injuries at a level distal to the first branch to the triceps and proximal to the posterior interosseous nerve were retrospectively studied. After a follow-up of at least 1 year, 24 patients (73%) obtained M3+ wrist extension, 16 (48%) obtained M3+ finger extension and only ten (30%) obtained M3+ thumb extension. Univariate, multivariate and receiver operating characteristic analyses showed that a delay in the repair of less than 6 months, a defect length of less than 5 cm or when grafted with three or more donor nerve cables achieved better recovery. Number of cables used was related to muscle strength recovery but not time to reinnervation. Nerve grafting for high radial nerve injury achieved relatively good wrist extension but poor thumb extension and is affected by certain prognostic factors.        Level of evidence: IV.

Purpose: Glucose metabolism underpins diabetic cataracts (DCs), but the relationship between the two remains unclear. Here, we tested the aqueous humour (AH) of patients with DCs to elucidate glucose metabolite levels., Methods: In this study, aqueous humour (AH) samples were collected preoperatively from DC eyes (n = 37) and age-related cataract eyes (n = 37) from 74 patients (74 eyes) undergoing uncomplicated cataract surgery. The content of glucose, pyruvate, L-lactate were detected by biochemical methods and advanced glycation end-products (AGEs) was detemined using enzyme-linked immunosorbent assay (ELISA) technique. Furthermore, the ratios of glucose/pyruvate and L-lactate/pyruvate in the AH were calculated. In addition, we calculated the correlation between glucose levels and AGEs in the AH., Results: The concentrations of glucose, pyruvate and AGEs in the DC group were higher than those in the control group. Significantly lower levels of L-lactate in the AH were found in the DC group. We calculated the glucose/pyruvate ratio and the L-lactate/pyruvate ratio in the AH, which showed that glucose metabolism was changed in the AH from DC patients. Interestingly, we observed that AGEs in the AH were significantly correlated with increased anterior chamber glucose permeability. A stronger correlation was found in the subgroups of male patients, younger patients, and patients with poor glycaemic control status., Conclusions: Comparison of the levels of glucose metabolism-related products in the AH in the DC group highlight a potential pathological mechanism for DC from a glucose metabolism perspective. The findings indicated an alteration in the metabolic pathways of energy metabolism and amino acids in the AH of DC patients.

Objective: To conduct a preliminary study on joint injuries of anterior and calcaneal fibular ligaments of the lateral ankle joint, and to analyze mechanism of action of shaking and poking in treating ankle joint and biomechanical properties of ankle during the recovery of joint injuries., Methods: CT scan was performed on a male volunteer with right ankle sprain. Mimics 10.0, Solidworks 2016, Hypermesh 12.0 and Abaqus 6.13 software were used to establish 3D nonlinear finite element analysis model of foot and ankle, and the validity of model was verified. Combined with clinical study, the finite element simulation analysis was carried out on the toe flexion, dorsiflexion, varus and valgus of ankle joint under different treatment periods by adjusting elastic modulus of ligament to simulate ligament injury., Results: With the treatment of shake and prick and recovery of ligament injury, the maximum stress and area with large stress on tibial pitch and fibular joint surface gradually increased under the four working conditions, and the stress value of the maximum stress ligament gradually increased, and the stress of the anterior and calcaneal fibular ligament dispersed and transferred, and the axial force gradually decreased., Conclusion: The finite element method was used to simulate the mechanical condition of the shaking and stamping technique, and the changes of the forces of the ligament and articular surface before and after treatment of anterior and calcaneal ligament combined injury of ankle talus were intuitively observed. The treatment effect was quantified, and could provid objective and scientific basis for clinical promotion and application of this technique.

Multifarious molecular ferroelectrics with multipolar axial characteristics have emerged in recent years, enriching the scenarios for energy harvesting, sensing, and information processing. The increased polar axes have enhanced the urgency of distinguishing different polarization states in material design, mechanism exploration, etc. However, conventional methods hardly meet the requirements of in situ, fast, microscale, contactless, and nondestructive features due to their inherent limitations. Herein, SHG polarimetry is introduced to probe the multioriented polarizations on a nanosized multiaxial molecular ferroelectric, i.e., TMCM-CdCl 3 nanoplates, as an example. Combined with the analysis of the second-order susceptibility tensor, SHG polarimetry could serve as an effective method to detect the polarization orders and domain distributions of molecular ferroelectrics. Profiting from the full-optical feature, SHG polarimetry can even be performed on samples covered by transparent mediums, 2D materials, or thin metal electrodes. Our research might spark further fundamental studies and expand the application boundaries of next-generation ferroelectric materials.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder primarily affecting cognitive functions. However, sensory deficits in AD start to draw attention due to their high prevalence and early onsets which suggest that they could potentially serve as diagnostic biomarkers and even contribute to the disease progression. This literature review examines the sensory deficits and cortical pathological changes observed in visual, auditory, olfactory, and somatosensory systems in AD patients, as well as in various AD animal models. Sensory deficits may emerge at the early stages of AD, or even precede the cognitive decline, which is accompanied by cortical pathological changes including amyloid-beta deposition, tauopathy, gliosis, and alterations in neuronal excitability, synaptic inputs, and functional plasticity. Notably, these changes are more pronounced in sensory association areas and superficial cortical layers, which may explain the relative preservation of basic sensory functions but early display of deficits of higher sensory functions. We propose that sensory impairment and the progression of AD may establish a cyclical relationship that mutually perpetuates each condition. This review highlights the significance of sensory deficits with or without cortical pathological changes in AD and emphasizes the need for further research to develop reliable early detection and intervention through sensory systems., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhang, Zhang, Zhang, Tao and Zhang.)

Persistent organic pollutants (POPs) in the environment have the characteristics of persistence, bioaccumulation, teratogenicity, carcinogenicity, and mutagenicity. Long-term exposure of low-content POPs will also have a certain impact on marine ecosystems and human beings. The contents of three typical persistent organic pollutants[polycyclic aromatic hydrocarbons (PAHs), organochlorine pesticides (OCPs), and polycyclic biphenyls (PCBs)] of surface sediments were analyzed using gas chromatography and mass spectrometry (GC-MS) to assess the pollution characteristics of persistent organic pollutants in Boao coastal waters. The distribution and source of persistent organic pollutants were analyzed in this study, and the ecological risk was assessed using three different methods:the effect interval low/median method (ERL/ERM), mean effect interval median quotient method (M-ERM-Q), and mean potential impact concentration quotient method (M-PEC-Q). The results indicated that the contents (measured by dry weight) of ΣPAHs, ΣOCPs, and ΣPCBs in the study area were 4.5-367.50, 3.99-175.30, and ND-2.89 ng·g -1 , respectively, which were at a low level, and the overall distribution showed a trend of gradually increasing toward the sea. The results of POPs source analysis showed that the PAHs in the study area were mainly from the combustion of wood and coal. Among OCPs, the HCH was mainly from lindane, the historical land-based input had been completely degraded, and the DDT was mainly the traditional DDTs pesticides, with additional continuous DDT input. The PCBs were primarily pentachlorobiphenyls, which might have come from the release of paint on the bottom of the hull in the early stage of shipping and the peeling off of paint from old ships. The ecological risk assessment results showed that there was little difference among the assessment results of the three methods, which showed that only phenanthrene monomer of PAHs in the study area had a slight negative impact, and the DDT and the γ- HCH among PAHs would cause great ecological risk, whereas PCBs and other pollutants would not cause ecological risk. On the whole, the possibility of comprehensive ecological risk caused by the three pollutants was very small.

Accumulating evidence supports the hypothesis that white matter (WM) abnormalities are involved in the pathophysiology of bulimia nervosa (BN); however, findings from in vivo neuroimaging studies have been inconsistent. We aimed to investigate the possible brain WM alterations, including WM volume and microstructure, in patients with BN. We recruited 43 BN patients and 31 healthy controls (HCs). All participants underwent structural and diffusion tensor imaging. Differences in WM volume and microstructure were evaluated using voxel-based morphometry, tract-based spatial statistics, and automated fibre quantification analysis. Compared with HCs, BN patients showed significantly decreased fractional anisotropy in the middle part of the corpus callosum (nodes 31-32) and increased mean diffusivity in the right cranial nerve V (CN V) (nodes 27-33 and nodes 55-88) and vertical occipital fasciculus (VOF) (nodes 58-85). Moreover, we found decreased axial diffusivity in the right inferior fronto-occipital fasciculus (node 67) and increased radial diffusivity in the CN V (nodes 22-34 and nodes 52-89) and left VOF (nodes 60-66 and nodes 81-85). Meanwhile, WM microstructural changes were correlated with patients' clinical manifestations. We did not find any significant differences in WM volume and the main WM fibre bundle properties between BN patients and HCs. Taken together, these findings provide that BN shows significant brain WM reorganization, but primarily in microstructure (part of WM fibre bundle), which is not sufficient to cause changes in WM volume. The automated fibre quantification analysis could be more sensitive to detect the subtle pathological changes in a point or segment of the WM fibre bundle., (© 2023 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

This was a phase 1 dose-escalation study of ZR202-CoV, a recombinant protein vaccine candidate containing a pre-fusion format of the spike (S)-protein (S-trimer) combined with the dual-adjuvant system of Alum/CpG. A total of 230 participants were screened and 72 healthy adults aged 18-59 years were enrolled and randomized to receive two doses at a 28-day interval of three different ZR202-CoV formulations or normal saline. We assessed the safety for 28 days after each vaccination and collected blood samples for immunogenicity evaluation. All formulations of ZR202-CoV were well-tolerated, with no observed solicited adverse events ≥ Grade 3 within 7 days after vaccination. No unsolicited adverse events ≥ Grade 3, or serious adverse events related to vaccination occurred as determined by the investigator. After the first dose, detectable immune responses were observed in all subjects. All subjects that received ZR202-CoV seroconverted at 14 days after the second dose by S-binding IgG antibody, pseudovirus and live-virus based neutralizing antibody assays. S-binding response (GMCs: 2708.7 ~ 4050.0 BAU/mL) and neutralizing activity by pseudovirus (GMCs: 363.1 ~ 627.0 IU/mL) and live virus SARS-CoV-2 (GMT: 101.7 ~ 175.0) peaked at 14 days after the second dose of ZR202-CoV. The magnitudes of immune responses compared favorably with COVID-19 vaccines with reported protective efficacy.

Topological data analysis (TDA) is an emerging field in mathematics and data science. Its central technique, persistent homology, has had tremendous success in many science and engineering disciplines. However, persistent homology has limitations, including its inability to handle heterogeneous information, such as multiple types of geometric objects; being qualitative rather than quantitative, e.g., counting a 5-member ring the same as a 6-member ring, and a failure to describe non-topological changes, such as homotopic changes in protein-protein binding. Persistent topological Laplacians (PTLs), such as persistent Laplacian and persistent sheaf Laplacian, were proposed to overcome the limitations of persistent homology. In this work, we examine the modeling and analysis power of PTLs in the study of the protein structures of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike receptor binding domain (RBD). First, we employ PTLs to study how the RBD mutation-induced structural changes of RBD-angiotensin-converting enzyme 2 (ACE2) binding complexes are captured in the changes of spectra of the PTLs among SARS-CoV-2 variants. Additionally, we use PTLs to analyze the binding of RBD and ACE2-induced structural changes of various SARS-CoV-2 variants. Finally, we explore the impacts of computationally generated RBD structures on a topological deep learning paradigm and predictions of deep mutational scanning datasets for the SARS-CoV-2 Omicron BA.2 variant. Our results indicate that PTLs have advantages over persistent homology in analyzing protein structural changes and provide a powerful new TDA tool for data science.

Protein engineering is an emerging field in biotechnology that has the potential to revolutionize various areas, such as antibody design, drug discovery, food security, ecology, and more. However, the mutational space involved is too vast to be handled through experimental means alone. Leveraging accumulative protein databases, machine learning (ML) models, particularly those based on natural language processing (NLP), have considerably expedited protein engineering. Moreover, advances in topological data analysis (TDA) and artificial intelligence-based protein structure prediction, such as AlphaFold2, have made more powerful structure-based ML-assisted protein engineering strategies possible. This review aims to offer a comprehensive, systematic, and indispensable set of methodological components, including TDA and NLP, for protein engineering and to facilitate their future development.

Recently, in order to comprehensively promote the development of medical institutions and solve the nationwide problems in the healthcare fields, the government of China developed an innovative national policy of "Trinity" smart hospital construction, which includes "smart medicine," "smart services," and "smart management". The prototype of the evaluation system has been established, and a large number of construction achievements have emerged in many hospitals. In this article, the summary of this field was performed to provide a reference for medical workers, managers of hospitals, and policymakers., Competing Interests: MG was employed by Digital Health China Co. Ltd. H-JL were employed by Shenyang Medical & Film Science and Technology Co. Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhang, Gong, Li, Wang and Gong.)

Small data are often used in scientific and engineering research due to the presence of various constraints, such as time, cost, ethics, privacy, security, and technical limitations in data acquisition. However, big data have been the focus for the past decade, small data and their challenges have received little attention, even though they are technically more severe in machine learning (ML) and deep learning (DL) studies. Overall, the small data challenge is often compounded by issues, such as data diversity, imputation, noise, imbalance, and high-dimensionality. Fortunately, the current big data era is characterized by technological breakthroughs in ML, DL, and artificial intelligence (AI), which enable data-driven scientific discovery, and many advanced ML and DL technologies developed for big data have inadvertently provided solutions for small data problems. As a result, significant progress has been made in ML and DL for small data challenges in the past decade. In this review, we summarize and analyze several emerging potential solutions to small data challenges in molecular science, including chemical and biological sciences. We review both basic machine learning algorithms, such as linear regression, logistic regression (LR), k -nearest neighbor (KNN), support vector machine (SVM), kernel learning (KL), random forest (RF), and gradient boosting trees (GBT), and more advanced techniques, including artificial neural network (ANN), convolutional neural network (CNN), U-Net, graph neural network (GNN), Generative Adversarial Network (GAN), long short-term memory (LSTM), autoencoder, transformer, transfer learning, active learning, graph-based semi-supervised learning, combining deep learning with traditional machine learning, and physical model-based data augmentation. We also briefly discuss the latest advances in these methods. Finally, we conclude the survey with a discussion of promising trends in small data challenges in molecular science.

Accurate segmentation of interstitial lung disease (ILD) patterns from computed tomography (CT) images is an essential prerequisite to treatment and follow-up. However, it is highly time-consuming for radiologists to pixel-by-pixel segment ILD patterns from CT scans with hundreds of slices. Consequently, it is hard to obtain large amounts of well-annotated data, which poses a huge challenge for data-driven deep learning-based methods. To alleviate this problem, we propose an end-to-end semi-supervised learning framework for the segmentation of ILD patterns (ESSegILD) from CT images via self-training with selective re-training. The proposed ESSegILD model is trained using a large CT dataset with slice-wise sparse annotations, i.e., only labeling a few slices in each CT volume with ILD patterns. Specifically, we adopt a popular semi-supervised framework, i.e., Mean-Teacher, that consists of a teacher model and a student model and uses consistency regularization to encourage consistent outputs from the two models under different perturbations. Furthermore, we propose introducing the latest self-training technique with a selective re-training strategy to select reliable pseudo-labels generated by the teacher model, which are used to expand training samples to promote the student model during iterative training. By leveraging consistency regularization and self-training with selective re-training, our proposed ESSegILD can effectively utilize unlabeled data from a partially annotated dataset to progressively improve the segmentation performance. Experiments are conducted on a dataset of 67 pneumonia patients with incomplete annotations containing over 11,000 CT images with eight different lung patterns of ILDs, with the results indicating that our proposed method is superior to the state-of-the-art methods.

Pain is a significant global health issue, and the current treatment options for pain management have limitations in terms of effectiveness, side effects, and potential for addiction. There is a pressing need for improved pain treatments and the development of new drugs. Voltage-gated sodium channels, particularly Nav1.3, Nav1.7, Nav1.8, and Nav1.9, play a crucial role in neuronal excitability and are predominantly expressed in the peripheral nervous system. Targeting these channels may provide a means to treat pain while minimizing central and cardiac adverse effects. In this study, we construct protein-protein interaction (PPI) networks based on pain-related sodium channels and develop a corresponding drug-target interaction (DTI) network to identify potential lead compounds for pain management. To ensure reliable machine learning predictions, we carefully select 111 inhibitor datasets from a pool of over 1,000 targets in the PPI network. We employ three distinct machine learning algorithms combined with advanced natural language processing (NLP)-based embeddings, specifically pre-trained transformer and autoencoder representations. Through a systematic screening process, we evaluate the side effects and repurposing potential of over 150,000 drug candidates targeting Nav1.7 and Nav1.8 sodium channels. Additionally, we assess the ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties of these candidates to identify leads with near-optimal characteristics. Our strategy provides an innovative platform for the pharmacological development of pain treatments, offering the potential for improved efficacy and reduced side effects.

Background & Aims: The progress toward clinical translation of imaging biomarkers for mass-forming intrahepatic cholangiocarcinoma (MICC) is slower than anticipated. Questions remain on the biologic behaviour underlying imaging traits. We developed and validated imaging-based prognostic systems for resected MICCs with an appraisal of the tumour immune microenvironment (TIME) underpinning patient-specific imaging traits., Methods: Between January 2009 and December 2019, a total of 322 patients who underwent dynamic computed tomography/magnetic resonance imaging and curative-intent resection for MICC at three hepatobiliary institutions were retrospectively recruited, divided into training (n = 193) and validation (n = 129) datasets. Two radiological and clinical scoring (RACS) systems, one integrating preoperative variables and one integrating preoperative and postoperative variables, were developed using Cox regression analysis. We then prospectively analysed the TIME of tissue samples from 20 patients who met study criteria from January 2021 to December 2021 using multiplexed immunofluorescence., Results: Preoperative and postoperative MICC-RACS systems built on carbohydrate antigen 19-9, albumin, tumour number, radiological/pathological nodal status, pathological necrosis, and three radiological traits (arterial enhancement pattern, tumour boundary, and capsular retraction) demonstrated good performance in predicting disease-specific (C-statistic >0.80) and disease-free (C-statistic >0.75) survival that outperformed rival models and staging systems across study cohorts ( P <0.05 for all). Patients with MICC-RACS score of 0-2 (low risk), 3-5 (medium risk), and ≥6 (high risk) had incrementally worse prognosis after surgery. Significant differences in spatial distribution and infiltration level of immune cells were identified between arterial enhancement patterns. Enhanced infiltration of immunosuppressive regulatory T cells and M2-like macrophages at the invasive margin were noted in tumours with distinct boundary and capsular retraction, respectively., Conclusions: Our MICC-RACS systems are simple but powerful prognostic tools that may facilitate the understanding of spatially distinct TIMEs and patient-tailored immunotherapy approach., Impact and Implications: The progress toward clinical translation of imaging biomarkers for mass-forming intrahepatic cholangiocarcinoma (MICC) is slower than anticipated. Questions remain on the biologic behaviour of MICC underlying imaging traits. In this study, we proposed novel and easy-to-use tools, built on radiological and clinical features, that demonstrated good performance in predicting the prognosis either before or after surgery and outperformed rival models/systems across major imaging modalities. The characteristic radiological traits integrated into prognostic systems (arterial enhancement pattern, tumour boundary, and capsular retraction) were highly correlated with heterogeneous tumour-immune microenvironments, thereby renovating treatment paradigms for this difficult-to-treat disease., Competing Interests: The authors have no relevant financial or non-financial interests to disclose. Please refer to the accompanying ICMJE disclosure forms for further details., (© 2023 The Authors.)

Protein post-translational modifications (PTMs) are important regulators of protein functions and produce proteome complexity. SIRT1 has NAD + -dependent deacylation of acyl-lysine residues. The present study aimed to explore the correlation between lysine crotonylation (Kcr) on cardiac function and rhythm in Sirt1 cardiac-specific knockout (ScKO) mice and related mechanism. Quantitative proteomics and bioinformatics analysis of Kcr were performed in the heart tissue of ScKO mice established with a tamoxifen-inducible Cre-loxP system. The expression and enzyme activity of crotonylated protein were assessed by western blot, co-immunoprecipitation, and cell biology experiment. Echocardiography and electrophysiology were performed to investigate the influence of decrotonylation on cardiac function and rhythm in ScKO mice. The Kcr of SERCA2a was significantly increased on Lys120 (1.973 folds). The activity of SERCA2a decreased due to lower binding energy of crotonylated SERCA2a and ATP. Changes in expression of PPAR-related proteins suggest abnormal energy metabolism in the heart. ScKO mice had cardiac hypertrophy, impaired cardiac function, and abnormal ultrastructure and electrophysiological activities. We conclude that knockout of SIRT1 alters the ultrastructure of cardiac myocytes, induces cardiac hypertrophy and dysfunction, causes arrhythmia, and changes energy metabolism by regulating Kcr of SERCA2a. These findings provide new insight into the role of PTMs in heart diseases., Competing Interests: Declaration of competing interest Authors have no conflicts of interest., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Weather-adaptive energy harvesting of omnipresent waste heat and rain droplets, though promising in the field of environmental energy sustainability, is still far from practice due to its low electrical output owing to dielectric structure irrationality and unscalability. Here we present atypical upcycling of ambient heat and raindrop energy via an all-in-one non-planar energy harvester, simultaneously increasing solar pyroelectricity and droplet-based triboelectricity by two-fold, in contrast to conventional counterparts. The delivered non-planar dielectric with high transmittance confines the solar irradiance onto a focal hotspot, offering transverse thermal field propagation towards boosted inhomogeneous polarization with a generated power density of 6.1 mW m -2 at 0.2 sun. Moreover, the enlarged lateral surface area of curved architecture promotes droplet spreading/separation, thus travelling the electrostatic field towards increased triboelectricity. These enhanced pyroelectric and triboelectric outputs, upgraded with advanced manufacturing, demonstrate applicability in adaptive sustainable energy harvesting on sunny, cloudy, night, and rainy days. Our findings highlight a facile yet efficient strategy, not only for weather-adaptive environmental energy recovery but also in providing key insights for spatial thermal/electrostatic field manipulation in thermoelectrics and ferroelectrics., (© The Author(s) 2023. Published by Oxford University Press on behalf of China Science Publishing & Media Ltd.)

Polypropylene (PP) has gained attention in the industry as an environmentally friendly material. However, its electrical properties are compromised due to space charge accumulation during operation, limiting its application in high-voltage DC cable insulation. This study investigates the effect and mechanism of SiO 2 with a DDS surface hydrophobic treatment on space charge suppression and the electrical properties of PP composites. The PP matrix was doped with SiO 2 nanostructures, both with a DDS surface hydrophobic treatment and untreated as a control group. The functional group structure and dispersion of nanostructured SiO 2 in the matrix were characterized. The findings reveal that the incorporation of SiO 2 nanostructures effectively mitigates charge accumulation in PP composites. However, a high concentration of unsurfaced nanostructures tends to agglomerate, resulting in inadequate space charge suppression and a diminished DC breakdown field strength. Nonetheless, surface treatment improves the dispersion of SiO 2 within the matrix. Notably, the composite containing 1.0 wt% of surface hydrophobic SiO 2 exhibits the least space charge accumulation. Compared to the base material PP, the average charge density is reduced by 83.9% after the 1800 s short-circuit discharges. Moreover, its DC breakdown field strength reaches 3.45 × 10 8 V/m, surpassing pure PP by 19.4% and untreated SiO 2 /PP composites of the same proportion by 24.0%.

Background: The current nodal (pN) classification still has limitations in stratifying the prognosis of small cell lung cancer (SCLC) patients with pathological classifications T1-2N0-2M0. Thus. This study aimed to develop and validate a modified nodal classification based on a multicenter cohort., Materials and Methods: We collected 1156 SCLC patients with pathological classifications T1-2N0-2M0 from the Surveillance, Epidemiology, and End Results database and a multicenter database in China. The X-tile software was conducted to determine the optimal cutoff points of the number of examined lymph nodes (ELNs) and lymph node ratio (LNR). The Kaplan-Meier method, the Log-rank test, and the Cox regression method were used in this study. We classified patients into three pathological N modification categories, new pN#1 (pN0-#ELNs > 3), new pN#2 (pN0-#ELNs ≤ 3 or pN1-2-#LNR ≤ 0.14), and new pN#3 (N1-2-#LNR > 0.14). The Akaike information criterion (AIC), Bayesian Information Criterion, and Concordance index (C-index) were used to compare the prognostic, predictive ability between the current pN classification and the new pN component., Results: The new pN classification had a satisfactory effect on survival curves (Log-rank P < 0.001). After adjusting for other confounders, the new pN classification could be an independent prognostic indicator. Besides, the new pN component had a much more accurate predictive ability in the prognostic assessment for SCLC patients of pathological classifications T1-2N0-2M0 compared with the current pN classification in the SEER database (AIC: 4705.544 vs. 4731.775; C-index: 0.654 vs. 0.617, P < 0.001). Those results were validated in the MCDB from China., Conclusions: The multicenter cohort developed and validated a modified nodal classification for SCLC patients with pathological category T1-2N0-2M0 after surgery. Besides, we propose that an adequate lymph node dissection is essential; surgeons should perform and consider the situation of ELNs and LNR when they evaluate postoperative prognoses of SCLC patients., (© 2023. The Author(s).)